Sighting means for target data acquisition are well known per se. These optical instruments are used by geodesists and by artillerists for example. Such equipment is comparable to a theodolite or transit compass, with a turntable for pointing a telescope toward a target. Typically, a compass, a computer with a CPU for running computer programs, an I/O unit, a memory, and a display device, or simply display, are included. Tilt and yaw angles from an observation site to a target are measured with a vernier. Most often, an active range-measuring device, such as an LRF, is also included.
It is taken for granted that modern sighting devices all include an optical device, e.g. a telescope or binoculars, and have to be powered-up and leveled before use. Optics, power-on, and leveling are standard and common practice in the art, and will therefore not be mentioned in the description below.
Also known in the art is the acronym DTM (digital terrain model), or DEM (digital elevation model) referring to a digitized topographic model, which provides a representation of a portion of terrain surface contour in the form of a three-dimensional digital map. Parties performing surface or volumetric calculations with respect to the modeled terrain, possibly make use of such a DTM. When the DTM is stored in a computer memory, it can be used as a unit in a terrain database. The stored DTM then provides the basic data for running surface and volumetric calculations implemented by a computer program associated with a computer and a computer memory. Various engineering, military and environmental related applications frequently refer to DTMs for surface or spatial calculations. A graphic illustration of a DTM is given in FIG. 1, to which reference is now made.
FIG. 1 shows a DTM surface S derived from a DTM database, associated with an (x,y,z) Cartesian-coordinate system, having a plane of grid points with (x,y) coordinates in the x-y plane. A (z) height-coordinate is defined for each discrete couple of (x,y) coordinates. Each point sampled on the terrain surface contour is represented by a junction of X and of Y lines in the grid. The height of each sampled point is given by values along the Z axis. The resolution of the sampling points of the DTM in the X-Y plane, and the accuracy of the height measurement of each sampled point depend on several factors, for example, on the quality of aerial photography from which the map was prepared.
In U.S. Pat. No. 5,086,396, Waruszewsky Jr. discloses “an aircraft navigation system” including “an inertial navigation system, a map of the terrain with elevation information stored in a digitized format as function of location, a typical energy managed of narrow (radar or laser) beam altimeter, a display system, and a central processing unit for processing data according to preselected programs.” This is an example of the use of a DTM for navigational purposes. Waruszewsky Jr. further points out that “The correct position of the aircraft with respect to the digitized map can permit the aircraft to engage in terrain following procedures using only the difficult to detect altitude range finding apparatus as a source of emitted electromagnetic radiation.” Hereby, Waruszewsky Jr. hereby refers to the problems associated with the detection of active sensors.
In U.S. Pat. No. 6,222,464, Tinkel et al. divulge “A method of automated scan compensation in a target acquisition system for reducing areas of potential threat surrounding an aircraft. The target acquisition system includes a scanning device with adjustable scan limits for scanning a desired area in the vicinity of the aircraft. “In their invention, Tinkel et al. make use of adjustable scanning limits to define a scanned area.
In the published US Patent Application No. 20020180636 A!, Lin, Chian-Fang, et al. teach a passive ranging/tracking processing method that provides information from passive sensors and associated tracking control devices and GPS/IMU integrated navigation system, so as to produce three dimensional position and velocity information of a target. The passive ranging/tracking processing method includes the procedure of producing two or more sets of direction measurements of a target with respect to a carrier, such as sets of elevation and azimuth angles, from two or more synchronized sets pf passive sensors and associated tracking control devices, installed on different locations of the carrier, computing the range vector measurement of the target with respect to the carrier using the two or more sets of direction measurements, and filtering the range vector measurement to estimate the three-dimensional position and velocity information of the target. Use is made of passive sensors, but there are needed two or more synchronized sets of passive sensors.
In U.S. Pat. No. 5,825,480, Udagawa recites “an observing apparatus which can instantly and correctly specify the current position of an object to be observed.”. Udagawa “computes the position at which a line extending from the own position to the observing direction initially crosses the surface of the earth.” and adds that “The coordinates of thus computed position represents the observation target, . . . ”. With Udagawa there is no mention of any computed position error due to errors inherent to input measurements, or of one or more error zones, or of hidden areas.
In U.S. Pat. No. 6,064,942, Johnson et al. recite “an enhanced precision forward observation system and method using a satellite positioning system receiver integrated with a laser range finder and a compass.” It is thus clearly stated in Johnson et al. that use is made of a laser range finder, which is an active range finding device that emits radiations, and cannot achieve passive range and data acquisition. Furthermore, Johnson et al. apply mathematical methods, including statistic computations and the use a Kalman filter that “allows multiple measurement integration as well as calculation of reliable error statistics”.
In “Terrain Intervisibility—Believe it or Not”, published in “The 19th 7-13 Oct. 2000 Proceedings”, the Digital Avionics Systems Conferences, Oct. 7, 2000, Peter N. Stiles makes no mention of passive range and data acquisition of a sighted target. Stiles recites intervisibility between an enemy and an aircraft with respect to terrain topography.
In “Computational Ground and Airborne Localization over Rough Terrain”, published in the Proceedings of the Computer Society Conference on Computer Vision and Pattern Recognition, Jun. 15, 1992, Yacoob et al. perform localization by use of an altimeter, a compass, an inclinometer and a range finder. Since active radiation-emitting equipment is used, there is no passive range acquisition involved. Nevertheless, Yacoob et al. recognize measurement errors which they define as an uncertainty cone, and define an active set, containing all the points on the surface of the DTM and within the elevation error range. Finally, Yacoob et al. test all the points on the terrain surface to determine if they fall within the uncertainty cone, and the visibility of all the points in the uncertainty cone is examined. Yacoob et al. do not recite passive range acquisition, do not recite an uncertainty area delimited by the intersection of the mantle of the uncertainty cone with the DTM, and do not display the uncertainty zone.
In U.S. Pat. No. 4,954,837, Baird et al. recite “Terrain Aided Passive Range Estimation”, “by which data as to the present position (including longitude, latitude, and altitude) and attitude of a sensor platform and stored terrain data are used to calculate an estimated range from the platform to a ground-based target or threat, and the estimated range is then processed by a Kalman filter to increase the accuracy of the calculated range. In accordance with the present invention, sensory angular data, owncraft positional data (i.e., data as to the position of the sensor platform), and stored digital terrain data are fused together to derive accurate threat/target location.”. Baird et al. explain that “The Kalman filter has better observability characteristics due to the availability of this pseudo-measurement of range derived from the line of sight (LOS) intersection with the stored terrain data base.”, and also that “Range estimation can be improved by processing multiple looks at a threat/target, using the motion of the platform to triangulate and using time integration of multiple measurements to filer noise, thereby improving passive target location estimation.”. It is thus clear that Baird et al. thus rely on line of sight intersection with the stored terrain database, the use of a Kalman filter, and do not calculate and recite an error area.
In GB Patent No. 2254214, George Brown recites an Imaging System using a radar altimeter, which is not a passive range acquisition device. Brown recites that “The range map derived by unit 12 is only approximate for reasons described above and hence bands of ranges are formed as shown in FIG. 3 rater than a series of discrete individual ranges. However, this level of accuracy is generally sufficient to be able to discriminate between different types of target object.”.
In view of the shortcomings of the prior art it is thus desirable to simply display to the operator the error zone or zones containing the target as well as hidden zones for the derivation of the true azimuth, the true North, and of the location data of the observation position.